1
DRY SEASON TEMPORAL VARIABILITY OF NITROGEN, PHOSPHORUS, AND
SEDIMENT IN RUNOFF FROM A RESIDENTIAL NEIGHBORHOOD
IN SOUTHERN CALIFORNIA
By
MARTI LYNN OCCHIPINTI
Advisor
DR GURPAL TOOR
NON-THESIS RESEARCH PAPER
UNIVERSITY OF FLORIDA
FALL 2012
2
TABLE OF CONTENTS
Abstract…………………………………………………………………………..….Page 3
1. Introduction…………………………………………………………………...….Page 4
2. Methods………………………………………………………………….……….Page 7
3. Results & Discussion………………………………………………........... ……Page 13
4. Conclusions…………………………………………………………….…….….Page 35
References………………………………………………………………..…...….…Page 37
3
ABSTRACT
In semi-arid climates, such as that of southern California, dry weather flows dominate for
more than half of the year and are driven by water runoff resulting from irrigation. The objective
of this study was to determine the temporal variation in nitrogen (N), phosphorus (P), and
sediment concentrations and loads in dry weather from a residential neighborhood (28 ha) using
intensive sampling techniques. Triple composite water samples were automatically collected at
3-hour intervals for one-week during June 2008 at the outlet pipe that drains the residential area.
Flow was recorded continuously from October 2007 through September 2008. Both flow and
nutrient concentrations increased and decreased in a daily cycle, with lowest values observed
from 6:00 a.m. to noon and highest values between 6:00 p.m. and midnight. Mean (n = 56)
concentrations of total N, total P, and total suspended solids (TSS) at the outlet pipe were 10.9,
1.3, and 52.2 mg L-1, respectively. The calculated dry season (153 day) export of total N, total P,
and TSS was 20.2, 2.3, and 97.1 kg ha-1, respectively. The dry season loading of N and P was
greater than most annual loading rates found in comparable runoff studies (TN: 5.0-23.9 kg ha-1
yr-1, TP: 0.4-2.3 kg ha-1 yr-1). Dry season load of TSS in this study was approximately 25% of the
annual rate found in a comparable study (TSS: 387 kg ha-1 yr-1). However mean concentration of
TSS during the one-week of intensive sampling was elevated. It is likely that additional input of
nutrients and sediment from the use of reclaimed water for irrigating common areas in the
evening and early morning hours as well as several transient events within the watershed caused
greater nutrient losses. The intensive sampling data from this semi-arid residential area suggests
that watershed nutrient export rates could be underestimated if water quality monitoring
assessments do not consider dry weather flows resulting from irrigation applications and the use
of reclaimed water within the watershed.
4
5
1. Introduction
Surface waters increasingly receive pollutants that diminish water resources. Previous
research has shown numerous negative impacts from anthropogenic activities on water quality
(e.g., Conley, 2009, Diaz, 2008). The scientific community has been investigating urban
stormwater runoff for the past several decades as local and state governments have been charged
with protecting surface and groundwater resources and creating total maximum daily loads
(TMDLs) for contaminants of concern for various water bodies. Nationwide studies have proven
too broad to predict activities occurring in local watersheds, although they have brought light to
the impacts of point and nonpoint source pollution on receiving waters (Rast and Lee, 1983;
USEPA, 1983b) Understanding the fate and transport of pollutants from land to water can allow
for the development and fine-tuning of best management practices (BMPs) to protect sensitive
water bodies and aquatic ecosystems.
Urban nonpoint and point source pollution have been identified as an important cause of
surface water quality degradation in the United States (Coulter, 2004; Easton, 2004; Foley, 2005;
Groffman, 2004; Pratt and Chang, 2012; USEPA, 1983b). Understanding the many factors that
contribute to urban surface water pollution will aid in the development of more accurate
pollutant loading estimates. Water running over the land’s surface carries contaminants such as
nutrients, nitrogen (N) and phosphorus (P), that enter adjacent water bodies causing harm to
aquatic ecosystems (Golterman, 1991; Goonetilleke, 2005; Nyenje et al., 2010; Yu et al., 2011).
Although N is a limiting nutrient in marine systems and P a limiting nutrient in freshwater
systems, estuarine systems can show N and P limitations at varying temporal and spatial scales
(Bergström, 2010; García-Pintado et al., 2007; Gin et al., 2011). Conley (2009) suggests that a
dual approach, that considers N:P ratios and seasonal shifts in limiting nutrients, when managing
6
N and P in surface waters may reduce water quality impacts and provide a more permanent
solution to protect water resources (Conley, 2009).
In urban systems, natural hydrology is significantly altered which amplifies runoff.
Urban development increases impervious (e.g. pavement and rooftops) surface area (ISA), which
decreases infiltration, increases runoff, and shortens the residence time of runoff water and
pollutants in the soil (Brion et al., 2011; Pfeifer and Bennett, 2011). Increasing ISA, reduces
opportunities for the breakdown and retention of pollutants by soil processes resulting in
increased pollutant concentrations in runoff (Brezonik and Stadelmann, 2002; Conley, 2009;
Lewis and Grimm, 2007). Other factors that influence runoff volume and pollutant
concentrations in the urban environment include climate and rainfall characteristics (antecedent
dry days and rainfall intensity), topography and geology (soil permeability and slope),
anthropogenic activities (irrigation and fertilizer application), and land classification (population
density and level of disturbance) within the watershed (Caccia and Boyer, 2007; Chua et al.,
2009; Line, 2002; Miguntanna et al., 2010; Roberts and Prince, 2010; Tomer, 2003). All these
factors exhibit great variability in urban areas making it difficult to draw comparisons from
existing studies.
To date, most water quality studies have examined runoff from broad land uses such as
forest, agricultural, and urban. This approach assumes that developed or urban land use is
spatially homogeneous within the watershed. A better approach would be to characterize land
uses within the urban drainage network. A typical urban watershed could contain land classified
as lawn, open space, parks, industrial, construction, commercial, golf courses, and high and low
density residential. The few studies that differentiate between urban land uses have shown that
the type of urban land affects both surface water flow and pollutant concentrations (Atasoy et al.,
7
2006; King et al., 2007; Line, 2002). More specifically classifying urban land uses will also
make it easier to predict possible pollutants and their sources.
In the urban landscape, pollutants of concern include nutrients, bacteria, industrial
chemicals, heavy metals, and sediments(Brown Gaddis et al., 2007; Conley, 2000; Miguntanna
et al., 2010). In a residential catchment, the main sources of these pollutants are lawn fertilizer,
vehicular traffic, atmospheric deposition, organic matter (i.e. lawn clippings), detergents,
recycled water used for irrigation, and pet waste (Carpenter et al., 1998; García-Pintado et al.,
2007; Law et al., 2004; Steele, 2010). Anthropogenic activities in the residential setting
influence not only the pollutant source, but also their possible transport to adjacent surface
waters. Regional variability associated with loading factors has illustrated the need for local
studies to more accurately estimate urban runoff pollution and assess the potential risk to surface
waters in the drainage network.
The objective of this study was to examine temporal variation in flow, nutrients (N and
P), sediment concentrations, and nutrient and sediment loads from a residential catchment using
intensive sampling. Interest in N and P stems from their key role as limiting nutrients for aquatic
systems (Diaz, 2008; García-Pintado et al., 2007). Suspended solids were analyzed to aid in
describing fluxes in nutrients due to the relationship between TSS and the organic and inorganic
forms of N and P (Bennett et al., 2001; Graves, 2004; Lado and Ben-Hur, 2009). This study is
limited to the urban residential land use as urbanization has hastened the conversion of pervious
rural land to impervious urban land (Foley, 2005; Vadeboncoeur et al., 2010). The hypothesis of
this study was that (1) intensive sampling in the residential catchment would illustrate patterns in
nutrient and sediment loads that are not detected with more conventional infrequent sampling
techniques (weekly, bi-weekly, or monthly grab samples) and (2) in semi-arid environments dry
8
weather near-continuous low flows can contribute significant amounts of nutrient and sediment
loads. This data will provide a better understanding of how residential land use contributes to
urban surface water pollution. If temporal cycles in residential runoff flow and nutrient
concentrations are detected, better sampling methods and more representative loading estimates
can be developed. This study also calculated nutrient loading during the dry season in a semi-
arid environment to expand current information on surface water contamination contributed to
annual nutrient export totals from non-storm events. Data from this study was compared to
existing urban runoff studies, although there were no other studies available for comparison that
focused specifically on residential dry weather nutrient concentrations.
2. Methods
This study analyzed data collected from a residential drainage area within a
predominately urban watershed. Water quality data was extracted from a larger study conducted
in Orange County, California (California, 2006). The larger study was designed to quantify
levels of various pollutants in residential runoff during dry weather and early season storm
events as well as evaluate BMPs to reduce pollutant loads. The complete study included four
residential sites of similar size, age, income, and demographics. This study focused on the only
site where intensive sampling was utilized and was limited to seasonal dry weather loading of
TN, nitrate-N, TP, orthophosphate-P, and TSS. Other water quality parameter data collected
were turbidity, electrical conductivity, and total organic carbon.
2.1 Site Description
This study was conducted in a coastal residential community in southern California located
in Orange County, California (Figure 1). The sampling location lies within the Aliso Creek
Watershed. The watershed is approximately 80 km south of Los Angeles and 105 km north of
9
San Diego. The main waterway within the watershed is Aliso Creek, which drains a long,
narrow coastal canyon with headwaters in the Cleveland National Forest. The creek ultimately
discharges into the Pacific Ocean at Aliso Beach. The watershed includes portions of the cities
of Aliso Viejo, Laguna Beach, Laguna Hills, Laguna Niguel, Laguna Woods, Lake Forest, and
Mission Viejo (County, 2006). The watershed covers approximately 7,844 ha with roughly
45.5% of the land (3,572 ha) classified as residential. The other major land uses are public
(2,385 ha, 30.4%) and commercial (964 ha, 12.3%) (Pappas, 2009). Water sampling conducted
in the watershed indicated that main contaminants of concern were bacteria, N, P, and Selenium
(CDM, 2009).
The watershed sampling location is set in the San Joaquin Hills, in the coastal northwestern
portion of California’s Peninsular Ranges geomorphic province. The San Joaquin Hills consist
primarily of Miocene and Pliocene age marine sedimentary rocks that have been uplifted,
faulted, and dissected by stream erosion (Consulting, 2007). The site itself is located on steep
and rocky terrain with slopes ranging from 15 to 75%. Major soils within the area are typically
clayey and have slow infiltration rates, which correlates to high runoff potential when wet. The
Bosanko-Balcom Complex with 15 to 30% slopes comprises 31.5% of the study area followed
by Soper-Rock Complex with 30 to 75% slopes (16.7% of area), and Balcom Clay with 15 to
30% slopes (11.8% of area) (NRCS, 2011).
The study area has a semi-arid climate with warm dry summers and cool wet winters.
Historic 40-year rainfall data from a local gauging station shows annual average precipitation of
approximately 38 cm. During the wet season, October to April, an average of 36 cm (95% of
annual precipitation) of rainfall occurs. The dry season occurs from May to September, and
average rainfall during this time is 2 cm (5% annual precipitation) (Crompton, 2006). Mean
10
annual air temperature during the dry season is 20° C and wet season mean temperature is 15° C.
The study site was a residential homeowners association (HOA) community consisting of
307 single-family homes constructed in the mid to late 1990’s (Haver, 2011). According the
U.S. Census Bureau, median household income in the study area was $95,498 during the time of
the study (Bureau, 2012). The parcels within the study were largely owner occupied and had
similar, mature, well-maintained yards. The selected site covered 28.13 ha of land. Commercial
multispectral aerial imagery from QuickBird (QB) and geographic information system (GIS)
raster analysis was used to classify land uses within the study site. It was determined that single-
family home sites occupied 53% (this includes homes, private yards, and driveways), streets
occupied 22%, and the remaining 25% was classified as other. Land classified as “other”
consisted mainly of common lawn and common green space. Impervious surface area for the
entire site included rooftops, driveways, and streets, and was estimated at 56% of total land area.
Residents of the single-family homes used potable water for landscape irrigation, while
common areas were managed by a property management company, hired by the HOA, and
irrigated with reclaimed water. According to data provided by the local water district, average
monthly potable household water use at the time of the study (summer, May to September 2008)
was 56,070 L. Monthly household average water use ranged from 48,100 L to 66,800 L with the
month of August having the highest household potable water use (District, 2011). Access to
reclaimed water use data during the time of the study was not obtained. To reduce the occurrence
of human contact with possible contaminants present in water the Southern Orange County
Water Authority (SOCWA) prohibited the use of reclaimed water for lawn irrigation between the
hours of 9:00 a.m. and 6:00 p.m. There were no restrictions on the use of reclaimed water to
irrigate sloped, non-turf landscapes in the study area. Although exact irrigation schedules could
11
not be determined for the site, it was noted that irrigation of common areas, with reclaimed water
occurred from 10:00 p.m. to 5:00 a.m. Most of the residential irrigation with potable water
occurred from 5:00 a.m. to 9:00 a.m. Runoff from the residential landscape collected in a gutter
system that was outfitted with a 107-cm storm outflow pipe that discharged water into the
drainage network of Aliso Creek Watershed. Flow was measured and water samples were
collected at the outlet of the outflow pipe prior to the water entering any tributary.
Figure 1. The residential study area within the Aliso Creek Watershed in southern California where one-week of intensive water quality sampling was conducted from June 16 to 23, 2008.
2.2 Flow Measurement
The outflow pipe in the study area had continuous flow, which was mainly attributed to
lawn irrigation during the dry season. Flow was measured at the 107-cm outflow pipe with an
automated in-situ flow meter (Hach Sigma 950Flowmeter, Hach Company, Loveland, Colorado).
The flow meter measured flow continuously at 2-min intervals from October 2007 through
12
September 2008. The flow meter collected data utilizing an area velocity sensor placed in the
bottom of the pipe. This method measures the mean velocity (V) of the water, as well as the
depth (using a bubbler), and determines flow (Q) based on the dimensions (A) of the outfall pipe
(Q= A × V) (Grant, 1997). No rainfall events occurred during the intensive sampling period of
one week (June 16 to 23, 2008). The flow meter was checked at weekly intervals and data were
downloaded. Due to the large volume of flow data collected, 2-min flow data were averaged into
hourly flows for the entire flow record. Recorded negative flows were considered erroneous and
omitted. Using the depth of flow and the size, shape, slope, and roughness of the channel, the
Manning formula is frequently used as a substitute or means of confirming unreliable field flow
data (Grant, 1997). It was determined that positive measured flows at the outflow pipe were
usable when compared to calculated flows using the following Manning formula:
where Q is the flow rate (L s-1), K is constant dependent on units, A is the cross sectional area of
the pipe (m2), R is the hydraulic radius (m)(an expression of A p-1, or cross sectional area of
water, A, divided by the wetted perimeter, p), S is pipe slope (m m-1), and n is a roughness
coefficient corresponding to the texture of the pipe (Manning, 1891). Constant low flows were
observed at the outflow pipe during the intensive sampling. Onsite observations using a float
indicated that runoff water from one irrigation event could reach the outflow pipe in less than 30
minutes.
2.3 Sample Collection and Processing
One-week of intensive water sampling was conducted at 3 h intervals starting at 9:00 a.m.
on June 16, 2008 and ending at 9:00 a.m. on June 23, 2008. The auto sampler (Hach Sigma
Q =KAR2 / 3S1/ 2
n
13
900Max Sampler, Hach Company, Loveland, Colorado) was calibrated to take a 300 mL sample
every hour and then create a triple composite sample of 900 mL every three hours. Water
samples were continuously collected at 3-hour intervals (8 samples per day) for 7 d, resulting in
56 samples for the whole week. Samples were removed from the auto sampler every 24 h. The
core of the sampling machine was iced and new ice was added every 24 h to maintain the
integrity of the samples.
After collection, samples were transferred on ice to the laboratory where Environmental
Protection Agency (EPA) standard analyses protocols were used to analyze total N (40 CFR
141), nitrate-N (EPA 350.1), total P (EPA 365.1), orthophosphate (EPA 365.3), total suspended
solids (TSS) (EPA 160.2) turbidity (EPA 180.1), electrical conductivity (EC), and total organic
carbon (TOC)(EPA 9060A)(USEPA, 1983a). Other-N (organic and ammonium) was calculated
as difference between TN and nitrate-N. Other-P (particulate and organic) was calculated as
difference between TP and orthophosphate. Nutrients (N and P) are pollutants of concern as the
watershed is listed in the EPA’s 303(d) list of the Clean Water Act. It is common for water
quality samples and flow data to be taken infrequently (monthly or less) throughout the year. In
this study, one-week of intensive sampling was conducted to determine if this method gives a
comparable picture of nutrient transport and loading to surface waters or if there is additional
information that can be gained by increasing the frequency of sampling.
2.4 Calculating Nutrient Loads
Dry season nutrient export rates and loading estimates were calculated for TN, TP, and
TSS. Dry season export rates were calculated on a per hectare basis for the study site. Loading
estimates assumed a dry season of 153 days (May to September). Export rates were calculated by
multiplying mean nutrient concentrations by the mean flow recorded during the intensive
14
sampling period. This averaging method is called the “simple method” for estimating nutrient
loading and is widely used in water quality monitoring studies. The “simple method” is well
suited for short-term studies and has proven to be a robust method for baseflow estimates
(Endreny et al., 2005; Johnson et al., 1998; Li et al., 2003). The equation used is as follows:
where is the dry season (153 d) loading rate for site k, for constituent i, in kilograms per
hectare (kg ha-1). is the averaged sampled dry weather flow from site, k, in liters per second
(L s-1), is the average measured concentration of constituent, i, from site, k, in milligrams per
liter (mg L-1), and Le is the total area of the site in hectares (ha). Temporal variation in nutrient
loading for each constituent was calculated by multiplying the 3-h composite constituent
concentration with the averaged 3-h flow.
3. Results & Discussion
3.1 Flow Dynamics
Averaged flow during the entire 2008 dry season (May to September) ranged from 0 to
nearly 30 L s-1, with a mean value of 3.10 L s-1. The mean flow for the intensive sampling
period of one-week (June 16 to 23, 2008) was slightly higher (3.96 L s-1) than the mean dry
season and mean flows recorded for the individual months (Table 1). It is likely that the
difference between mean flow for the intensive sampling period and mean flows for the
individual months was caused by an increase in irrigation and handwatering prompted by
extreme heat during the week of intensive sampling. During the intensive sampling period,
minimum and maximum flow was 1.55 L s-1 and 7.23 L s-1, respectively. The intensive sampling
showed that flow rates increased and decreased diurnally, with the lowest flow measured each
Lk,ie
Qke
Ck,ie
Lk, ie =
QkeCk, i
e
Ae
15
day just before noon. After 12:00 p.m. flow at the outflow pipe continued to increase and the
maximum flow rate occurred each morning near 6:00 a.m. (Figure 2). This cycle was consistent
throughout the one-week intensive sampling period (Figure 2) as well as for the month of June
(Figure 3). This variation in daily flow is not uncommon. An urban runoff loading study
conducted in Los Angeles, California showed that dry weather flows in arid urban watersheds
can exhibit predictable daily variation with flows changing by 40% during the course of a single
day (Stein and Ackerman, 2007).
Flow data collected from this southern California site, during May through September
2008, showed that irrigation schedules dictated daily flow patterns in this semi-arid residential
drainage basin during the dry season. Variations in flow would be missed if the flow were not
measured with in-situ, time or flow sensitive, methods. Similar flow values and daily variability
in flow during one-week of intensive sampling and for the entire dry season flow (Figure 3)
indicated a representative snapshot of flow patterns for this residential drainage network was
captured with intensive sampling. Previous studies have shown that dry weather flows, or
baseflows, can be significant contributors to annual flows, especially in semi-arid climates. For
example, a study in Los Angeles estimated that dry weather flows contributed 10 to 50% of
annual flow, with greater contributions from dry weather flow occurring in years of little
precipitation (McPherson et al., 2005). Using the monthly mean flows measured in this
residential catchment from October 1, 2007 through September 30, 2008, it was estimated that
dry season flows (May to September) from this catchment contributed 37% of annual discharge,
while the wet season (October-April) contributed 63% (Table 1). Understanding the flow
patterns specific to the drainage network are essential in creating sampling protocols to capture
variability in pollutant transport.
16
Table 1. Mean recorded flow at the outflow pipe draining a southern California residential watershed during 2007-2008 wet and dry seasons.
Season Month Flow (L s-1) Total Flow (L)
Mean Range
Wet October 2007 1.93 0.02-49.45 516,131.20 November 2007 3.27 0.19-151.24 847,558.42 December 2007 2.65 0.01-99.97 710,055.36
January 2008 8.18 0.01-364.57 2,189,688.62
February 2008 4.15 0.01-168.39 1,003,051.30
March 2008 3.09 0.28-15.84 826,480.81
April 2008 3.64 0.38-12.60 942,319.14
Wet season 3.84 0.01-364-57 7,035,284.86 (63% of total)
Dry May 2008 3.53 0.08-29.80 945,297.56 June 2008 3.30 0.08-9.07 856,231.07 July 2008 3.75 0.15-17.46 100,4177.65
August 2008 2.92 0.14-8.61 781,871.26
September 2008 1.99 0.0-12.20 515,319.36
Dry season 3.10 0.0-29.80 4,102,896.90 (37% of total)
Week of intensive sampling 3.96 1.55-7.23 -
17
Figure 2. Measured flow at the outflow pipe draining a southern California residential watershed during an intensive sampling period of one-week from June 16 to 23, 2008.
Figure 3. Measured flow at the outflow pipe draining a southern California residential watershed for June 2008, with highlighted intensive sampling period of one-week, from June 16 to 23, 2008.
18
3.2 Variation in Nutrient Concentrations
The mean (n = 56) concentration of TN was 10.9 mg L-1, nitrate-N was 5.42 mg L-1, and
other-N (organic and ammonium) was 5.43 mg L-1. During the intensive sampling period
average composition of TN was 58% nitrate-N and 42% other-N (Table 2). During the sampling
period, the lowest concentrations of TN, nitrate-N, and other-N were 4.27, 2.42, and 0.09 mg L-1,
respectively. Nitrogen concentrations exhibited a diurnal pattern with highest concentrations
during each 24-hour period occurring between 8:00 p.m. and midnight, while lowest
concentrations occurred between 6:00 a.m. and noon each day (Figure 4). Nitrogen
concentrations in the beginning of the sampling period (June 16, 2008) were higher than those
sampled near the end of the sampling period (June 23, 2008).
Table 2. Concentrations of nitrogen, phosphorus, and total suspended solids at the outflow pipe draining a southern California residential watershed during one-week of intensive sampling in June 2008.
Nutrient Concentration Total N Nitrate-N Other-N Total P Orthophosphate Other-P TSS
mg L-1
Mean 10.85 5.42
(58%)a 5.43
(42%)a 1.27 0.82 (75%)a
0.45 (25%)a 52.18
Minimum 4.27 2.42 0.09 0.51 0.41 0.02 3.44 Maximum 29.80 9.50 21.82 7.47 1.79 7.06 274.36 Standard Deviation 6.34 1.72 5.24 1.03 0.36 1.00 59.11 adata in parentheses are average percent of total N or of total P during the intensive sampling.
Nearly 80% of samples collected contained 50% or more nitrate-N. Of 56 sampling
events, runoff from 18 sampling events recorded other-N (organic and ammonium-N) as the
dominant N form. Twelve of these samples coincided with the higher concentrations of TN that
occurred in the first two days (June 16 to June 18, 2008) of the sampling period. The high
concentration of other-N during the beginning of the sampling period coincides with weekend
19
gardening activities and the washdown of hardscapes by homeowners. Plant debris (organic-N)
being flushed into the drainage network, as well as the application of ammonium fertilizer and
compost, is a common contributor of nitrogen to urban runoff (Andrews, 1998; Groffman, 2004;
Vadeboncoeur et al., 2010). For the remainder of the intensive sampling period (June 19 to June
23, 2008), nitrate-N varied between 45% and 100% of TN, with the highest percentages of
nitrate-N occurring each day at around noon. Subsequently, other-N remained less than 60% of
TN with the highest contributions of other-N to TN occurring near midnight each 24-hour
period. Other water quality studies in urban areas showed variation in predominant N forms that
are dependent on N sources within the watershed (Caccia and Boyer, 2007; Yu et al., 2011). One
explanation of this diurnal switching of N forms could be the use of reclaimed water (treated
wastewater) on common areas in the residential community during nighttime hours. Reclaimed
water usually contains higher concentrations of ammonia than potable water (Asano, 1987;
Metcalf et al., 2007). Constituent concentrations of reclaimed water vary by source and
treatment (secondary, tertiary, or advanced wastewater treatment) and ammonia-N has been
shown to be the predominant form of N in some reclaimed water (Asano, 1987; Evanylo, 2010;
Metcalf et al., 2007; Taebi and Droste, 2004). Finally, it has been shown that diurnal variation in
nutrients can be controlled by biogeochemical processes, photosynthesis, and respiration in river
ecosystems (Iwanyshyn et al., 2008). More studies focused on characterizing chemical and
physical transformations of pollutants in urban drainage networks would aid in developing
appropriate BMPs to control nutrient losses (Barber et al., 2005).
20
Figure 4. Nitrogen concentrations in runoff collected from the outflow pipe draining a southern California residential watershed during an intensive sampling period of one-week from June 16 to 23, 2008.
The mean concentration of TN (10.9 mg L-1) found in this study was 40 to 200% higher
than residential runoff sampled during other water quality studies conducted throughout the
United States (Table 3). One study in North Carolina, measured water quality parameters from a
small residential catchment (2.54 ha) using 69 storm events over the period of 2.3 years, they
found an event mean concentration (EMC) for TN of 6.71 mg L-1 (Line, 2002). Although
reclaimed water is likely affecting TN concentration in the southern California residential
watershed, TN values from the two studies were comparable. One explanation for the closeness
of TN values in the North Carolina and southern California runoff studies could be attributed to
similarities in land classification and drainage network (gutter system), the relatively large
quantity of samples taken, and the small size of the watersheds. Studies that showed much lower
21
N concentrations were conducted with fewer samples, in areas with mixed land uses, and in
much larger watersheds (CDM, 2009; McPherson et al., 2005). Water quality studies have shown
that the size of the watershed can yield varying results for nutrient losses and that a large
watershed may provide more biogeochemical opportunities to capture and retain N, keeping it
from leaving the study area (Chua et al., 2009; Lewis and Grimm, 2007). There are several other
factors that may be influencing the elevated levels of N seen in this southern California
residential study, like seasonality in nutrient concentrations and the absence of storm events.
Water quality studies have found that many constituents show seasonal shifts as nutrient
sources change and biogeochemical processes in the watershed change (Beckert et al., 2011;
García-Pintado et al., 2007; Lewis and Grimm, 2007). Studies also show that N concentrations in
dry weather baseflows tend to be higher because storm flows can dilute N concentrations,
especially nitrate-N (Brion et al., 2011; Fan et al., 2012; Tsegaye et al., 2006). Samples from
this study were collected from baseflows during the summer, in a small watershed, conditions
which are conducive to increased concentrations of TN. Reclaimed water use within the study
site, an estimated impervious surface area of 56%, the sloped topography of the site, as well as
the clayey nature of the soil, likely contributed to the high mean TN concentration measured in
this catchment. It is important to note that even the minimum N concentration recorded during
one-week of intensive sampling was more than double the proposed nitrogen TMDL for the
Aliso Creek mainstem (1.0 mg L-1) (Watersheds, 2012). This information is important for water
quality managers trying to identify N pollution sources within the Aliso Creek Watershed. When
TN concentration from this study (10.9 mg L-1) was compared to dry weather TN concentration
(1.36 mg L-1) at the outlet of the Aliso Creek Watershed (Table 3) it was apparent that this
residential neighborhood is most likely a significant a contributor of TN within the watershed.
22
Table 3. Comparison of nitrogen, phosphorus, and total suspended solids concentrations in runoff collected from the outflow pipe draining a southern California residential watershed with runoff from data from previous studies.
Land Use TN (mg L-1)
TP (mg L-1)
TSS (mg L-1) Sampling Location Study Area Reference
Single Family Residential
6.71 a Mean EMCc
0.59 Mean EMCc
73 Mean EMCc
Automated flow-
weighted storm
runoff for 69 events
Nuese River
Basin, NC
2.54 ha 25% ISAb 2-10% slopes sandy loam
2.3 year
(Line, 2002)
Mixed Residential
2.14a-2.46a
Median EMCc
0.14-0.32
Median EMCc
24-61 Median EMCc
Periodic storm
sampling
Ballona Creek
Watershed, CA
30,180 ha 3 sites
channelized semi-arid 4 years (McPherson
et al., 2005) Mixed Residential
5.16a
Mean 0.63
Mean 19.5
Mean
18 dry weather
grab samples
Ballona Creek
Watershed, CA
30,180 ha 3 sites
combined channelized
semi-arid 4 years
Downstream (3km) from the study site
1.36a Mean
0.39 Mean
225 Mean
4 wet weather
grab samples
Outflow Aliso Creek
Watershed, CA
7,844 ha 45.5%
Residential downstream 2002-2005
(CDM, 2009) Downstream
(3km) from the study site
1.25 a
Mean 0.17
Mean 7.6
Mean
9 dry weather
grab samples
Outflow Aliso Creek
Watershed, CA
7,844 ha 45.5%
Residential downstream 2002-2005
Single Family Residential
10.85 Mean
1.27 Mean
52.18 Mean
Automated dry
weather intensive sampling
Aliso Creek
Watershed, CA
28.13 ha 15-30% slopes
56% ISAb
clayey semi-arid 1 Week
This Study
aTN is the sum of Nitrate-N and TKN bISA denotes Impervious Surface Area cEMC is mean concentration for flow weighted storm flows
23
Mean (n = 55) concentrations of TP, orthophosphate, and other-P (particulate-P, which
included organic and recalcitrant inorganic forms) were 1.27, 0.82, and 0.45 mg L-1, respectively
(Table 2). During the intensive sampling period the average composition of TP was 75%
orthophosphate-P and 25% other-P. All forms of P reached daily maximum concentrations
between 6:00 p.m. to midnight with the exception of one event where TP sampled was nearly 6-
times the recorded mean. This increase in TP occurred at noon on June 19, 2008 and was
comprised of almost entirely other-P (95%) (Figure 5). This event had little effect on
orthophosphate and indicated that other-P (particulate-P) was washed (flushed) into the drainage
network by anthropogenic activities, mimicking the “first flush” phenomena.
Figure 5. Phosphorus concentrations in runoff collected from the outflow pipe draining a southern California residential watershed during an intensive sampling period of one-week from June 16 to23 2008.
24
Studies have shown that between rain (or irrigation) events, solids accumulate on the
surface of the drainage network. When substantial wetting occurs (e.g. storm or hosing off of
driveway) there is a marked increase of certain constituent concentrations as these solids are
flushed off of the urban surface and into drainage system. Studies show that response to “first
flush” is greatest for TSS>TP>TN, with particulate and organic forms of P and N being more
mobile during this time than their dissolved inorganic counterparts (Beckert et al., 2011; Gray,
2004; Kim et al., 2007; Obermann et al., 2007). Although it is not possible to say for certain
whether the two events are related, there was also a spike (5 times the mean concentration) in
TSS 12-h prior to the noted increase in TP; there was no response in TN during this time. It is
possible that sediment and organic material (TSS) transported during the runoff event also
transported particulate-P but at a varied time scale influenced by change in flow intensity,
suspended particle size, and the speciation of P (Daroub, 2002; Uusitalo et al., 2000). Studies
show that particulate-P is the dominant form in urban runoff and that accumulation of P in urban
regions is mainly a surface problem, whereby particulate-P, associated with the finer fraction (1-
25 microns) of sediment, accumulates on impervious surfaces and is then transported into surface
waters by rain or irrigation events (Bennett et al., 2001; Forsberg, 1995; Johannesson et al.,
2011; Vaze and Chiew, 2002). For example, in this southern California residential watershed,
particulate-P and other solids accumulate on driveways and sidewalks. During the dry season,
transport occurs when this build-up is washed into the drainage network by human activities or
irrigation. This type of unpredictable anthropogenic activity is sometimes referred to as a
transient event. Transient events are significant contributors to nutrient loss form urban
environments and can drive up mean constituent values (Lee et al., 2009; Lim, 2003).
25
In this residential watershed, daily P loss was predominately orthophosphate-P. For 91%
of the one-week sampling period, orthophosphate-P comprised 50% or more of TP.
Orthophosphate-P is probably associated with reclaimed water used within the residential
watershed, as treated wastewater is known to have higher levels of orthophosphate compared to
natural or potable water (Asano, 1987; Endreny et al., 2005; Metcalf et al., 2007; Metcalf, 1916).
There were two separate occasions (June 19 and June 21, 2008) where other-P was the
predominant form of P in this study. During these two events, P associated with organic matter
and the fine fraction of soil sediment was transported with the residential runoff. Although only
five runoff samples showed TP to be primarily composed of other-P, this increase in particulate-
P was responsible for driving up mean TP concentrations and more than quadrupling P loss
during the event. Reclaimed water is contributing to P loss from our catchment as highest TP
concentrations in this residential watershed corresponded to the recommended hours of
reclaimed water use (6:00 p.m. to 9:00 a.m.). However, during the sampling period of one-week,
the transient event (increase in other-P and TP concentration) captured with intensive sampling
was exerting a greater influence on mean TP concentration than reclaimed water usage.
Mean TP concentration from the site was high when compared to other residential water
quality studies (Table 3). For comparison, one study estimated a mean TP concentration of 0.63
mg L-1, which is 50% the concentration (1.27 mg L-1) found in the southern California residential
watershed study. The previous study was conducted in a mixed residential area, the Ballona
Creek Watershed in Los Angeles, California. In this large watershed (30,180 ha) mean TP
concentration was calculated using 18 dry weather samples (collected during 1 summer) and
existing flow data (4 years) (McPherson et al., 2005). Fewer samples collected and the large size
of the watershed help to explain why the mean TP concentration from the Ballona Creek
26
Watershed was lower than the value found in the southern California residential watershed. The
mean concentration of TP found in this residential study was 13-times greater than the proposed
TMDL of 0.1 mg L-1 that applies to the Aliso Creek mainstem and several tributaries
(Watersheds, 2012), including the tributary adjacent to the residential outflow pipe. Total P
concentration at the outflow pipe was 7-times greater than the dry weather concentration of TP
(0.17 mg L-1) found downstream (3 km) from the residential site, proving again that this
community is a source of nutrient enrichment to the Aliso Creek Watershed (CDM, 2009).
Mean (n = 56) TSS for the one-week sampling period was 52.2 mg L-1. There was a
noted increase in TSS midway through (June 18, 2008) the intensive sampling when TSS
reached close to 300 mg L-1 (Figure 6). This event could be linked to the increase in TP and
other-P, concentrations because particulate P has been shown to positively correlate with
turbidity and TSS (Chua et al., 2009; Daroub, 2002; Graves, 2004; Uusitalo et al., 2000). For the
rest of the sampling period, TSS concentrations were below 100 mg L-1 (Figure 6). Highest
concentrations of TSS often occurred between 8:00 p.m. and 6:00 a.m., which corresponds to the
recommended irrigation times for reclaimed water.
27
Figure 6. Total suspended solids concentrations and turbidity in runoff collected at the outflow pipe draining a southern California residential watershed during an intensive sampling period of one-week from June 16-23 2008.
Reclaimed water used in southern California has been shown to contain increased levels
of TSS (Asano, 1987). Lowest concentrations for TSS mirrored reduced flows in the catchment
with lowest values occurring at noon each day. Irrigation runoff and transient anthropogenic
events (e.g. car washing, erosion from slopes, construction, and washing of impervious surfaces)
are the primary mechanism for TSS transport in this residential study area. Sediment loss is a
function of soil properties, land management, and water characteristics. The steep and sustained
slopes in this residential watershed are conducive to erosion if not properly managed. Because
TSS transport is related to the intensity and duration of runoff events, a decrease in TSS
concentration (<20 mg L-1) occurred when irrigation ceased each day (near noon) and flow
dropped to less than 2.0 L s-1. Comparison of mean TSS from this study with other residential
28
runoff studies found that dry weather concentration from the southern California residential site
was more similar to concentrations found in studies that conducted wet weather or storm
sampling (Table 3). Similar results were found from the small (2.54 ha) residential catchment in
North Carolina where 69 storm events were sampled to calculate an EMC of 73 mg L-1for TSS.
The dry weather mean TSS concentration from this study was comparable to storm TSS
concentrations, suggesting that the “first flush” phenomena can be caused by irrigation and
anthropogenic activities at the catchment scale, especially in watersheds with sloped topography
that contain soils of low infiltrability.
3.3 Reclaimed Water Use in the Watershed
Reclaimed water has become increasingly important in the water scarce southwest. In an
effort to conserve high quality potable water, the use of reclaimed water as an alternative source
for landscape and agricultural irrigation has become vital to states like California and Florida.
Proper management of reclaimed water for irrigation is crucial as reclaimed water is inherently
higher in nutrients, suspended solids, dissolved organic matter, and soluble salts (Lado and Ben-
Hur, 2009; Metcalf et al., 2007). These additional inputs in the urban landscape can hinder plant
growth, alter the soil structure, and lead to increased nutrient losses as this study illustrates.
Because reclaimed water quality parameters vary by treatment type as well as effluent source, a
range of constituent concentrations found in select treatment facilities in California (Asano,
1987) is presented along with potable water quality parameters (Table 4). Potable water data was
compiled from the most recent District Water Quality Report (District, 2012) and from a study
conducted where potable and reclaimed water was used to irrigate turfgrass plots (Evanylo,
2010). Information from the turfgrass study was necessary for comparison, as data related to
potable (tap) water nutrient concentrations is very limited.
29
Table 4. Comparison of water quality parameters among residential runoff from this study, treated wastewater (reclaimed water), and potable water from various sources.
Water Quality Constituent Residential Runoff
Reclaimed water (secondary and
tertiary treatment) Potable water
pH 8.15 6.8-7.6 7.0-8.6a
EC (dS m-1) 2.11 1.02-1.44 0.27b
Total nitrogen (mg L-1) 10.85 17.2-24.9 1.4b
NH4-N (mg L-1) -a 1.4-25 -
NO3-N (mg L-1) 5.66 0.7-21.3 0-0.4a
Organic-N (mg L-1) -a 0.2-2.6 - Total phosphorus (mg L-1) 1.26 12.5 .25b
Orthophosphate-P (mg L-1) 0.83 3.4-30.8 -
Total dissolved Solids (mg L-1) 1350 476-940 440-490a
Total Suspended Solids (mg L-1) 52.18 1-26 1.0b
Reference Mean runoff
concentrations from this study
Mean concentration ranges from select
treatment facilities in California (Asano, 1987)
a=Moulton Niguel Water Quality Data (District, 2012)
b= water used to irrigate turfgrass plots in Virginia
(Evanylo, 2010) aMean values of NH4-N plus Organic-N were 5.2.
The mean concentrations of nutrients found in this study for were elevated as a result of
reclaimed water use within the residential watershed as well as unpredictable human activities.
The mean TSS concentration found in runoff from this residential study was high compared to
concentrations typically found in reclaimed water. Although reclaimed water may be a source
of TSS in this watershed, transport caused by anthropogenic activities within the catchment
played a bigger role in TSS losses. The mean TN and nitrate-N concentrations from this study
30
are comparable to the concentrations exhibited by reclaimed water. During the one-week of
intensive sampling it would appear that reclaimed water use had the greatest effect on TN losses
from this catchment. The mean concentrations of TP and orthophosphate from this study were
lower than usually found in reclaimed water. No information on particulate P (the primary
source during transient events) in reclaimed water could be found for comparison. TP loss from
this study was heavily influenced by transient events (possible construction or landscaping
activities) captured with intensive sampling as well as by reclaimed water use. Another indicator
that reclaimed water was influencing nutrient losses from this community was the extreme
salinity (soluble salts) and elevated total organic carbon (TOC) concentrations found during
hours of reclaimed water use. Electrical conductivity (EC) measured at the outflow pipe ranged
from 1.43 to 3.64 dS m-1, which is equivalent to about 915-2330 mg L-1 of total dissolved solids
(TDS). Mean concentration of TOC was 13.1 mg L-1 which is typical for wastewater that has
received secondary treatment (Metcalf et al., 2007). Frequently, lowest EC and TOC values
occurred at 6:00 a.m., which corresponds to the daily increase in potable water irrigation (Figure
8). Prolonged reclaimed water use in this residential catchment could lead to salt accumulation
at the soil surface. Adverse effects associated with soil salinity include lowered plant
productivity, decreased water infiltration by clogged soil pores and clay dispersion, and
increased runoff. Soil salinization commonly occurs in arid climates when adequate water is not
available to flush the salts deeper into the soil profile and is more prevalent in soils with high
clay content (Lado and Ben-Hur, 2009; Martinez, 2009; Metcalf et al., 2007).
31
Figure 8. Electrical conductivity and total organic carbon concentrations in runoff collected at the outflow pipe draining a southern California residential watershed during an intensive sampling period of one-week from June 16 to 23 2008.
3.4 Variation in Nutrient Loading Rates
Nutrient loading exhibited daily variations that were similar to flow and nutrient
concentrations. The mean loading rate for TN was 3.84 kg day-1 (Table 5). Lowest TN load
occurred from 6:00 a.m. to noon and highest loads frequently occurred from 6:00 p.m. to
midnight each day (Figure 7). The mean TP load was 0.44 kg day-1. Total P load was also lowest
from 6:00 a.m. to noon each day. Total P loads were elevated close to midnight with the
exception of one event where TP load was greatest at noon during the middle (June 19, 2008) of
the intensive sampling period. The mean loading rate for TSS was 19.7 kg day-1. Total
suspended solids load exhibited lowest values near noon each day and highest loads at various
times within recommended reclaimed water irrigation hours (6:00 p.m. and 9:00 a.m.). Like TP,
32
a significant increase in TSS load (nearly 6-times the mean rate) occurred in the middle (June 18,
2008) of the sampling period (Figure 7). As mentioned previously, unexplained transient events
created a flushing effect that is likely responsible for the increase in TSS and TP loads that
occurred during June 18 to June 19, 2008. Total suspended solids are closely related to turbidity
and this change in water quality during the middle of the intensive sampling period was
confirmed by turbidity (NTU) measurements (Figure 6). Total N loads increased in response to
an unknown event on June18 to June 20, 2008. Nutrient and sediment loading in this catchment
were related to anthropogenic activities and reclaimed water use within the site. With a few
exceptions, all constituents showed greatest losses during the recommended irrigation hours for
reclaimed water.
Table 5. Loads of nitrogen, phosphorus and total suspended solids in runoff collected at the outflow pipe draining a southern California residential watershed during one-week of intensive sampling in June 2008.
Loading Rates Total N Nitrate-N Other-N Total P Orthophosphate Other-P TSS
kg day-1
Mean 3.84 1.95
(51%)a 1.89
(49%)a 0.44 0.29 (66%)a
0.15 (34%)a 19.71
Minimum 0.80 0.44 0.02 0.09 0.07 0.01 0.62 Maximum 11.63 4.20 8.94 2.10 0.75 1.99 11.89 Standard Deviation 2.70 0.91 2.08 0.34 0.17 0.28 25.26
Simple Methodb 3.72 1.94 1.78 0.43 0.28 0.15 17.85 adata in parenthesis are percent of total N or total P load. bSimple method was calculated by multiplying the mean constituent concentration (mg L-1) by the mean flow (ls-1) for the one-week sampling period (Endreny et al., 2005; Johnson et al., 1998; Li et al., 2003).
33
Figure 7. Total nitrogen, phosphorus, and suspended solids loads in runoff collected at the outflow pipe draining a southern California residential watershed during an intensive sampling period of one-week from June 16-23 2008.
The dry season (153 d) nutrient export rates found were 20.2 kg N ha-1, 2.34 kg P ha-1,
and 97.1 kg TSS ha-1 (Table 6). Even though export rates from this southern California
residential watershed only account for 42% of the year, dry season nutrient export rates
calculated for TN and TP were higher than most annual nutrient export rates found in
comparable urban runoff studies (Table 6). Seasonal TN loading from the southern California
study was more than double any annual rate found by a literature review focused on developed
lands (Dodd, 1992). Total P export from the southern California residential watershed was 1.5-
times greater than any annual loading rate found by the same review. One study that had
comparable export rates was conducted in a small residential watershed (2.54 ha) in North
Carolina. Using the sum of all storm loads (69 events) divided by the duration of the sampling
34
period (2.3 years) and size of the watershed (2.54 ha), the North Carolina study found annual
export rates of 23.9, 2.3, and 387 kg ha-1 yr-1 for TN, TP, and TSS respectively (Line, 2002).
Conservatively, if one assumes that wet weather flows from the southern California residential
watershed contribute as much nutrients and sediment as dry weather flows, TN and TP export
from the site would still be double the rates found in North Carolina; TSS export would be about
half of the export rates found in the previous study. Result from the southern California
residential watershed show, that in a semi-arid climate, dry weather flows can make large
contributions to annual TN and TP loads. While the dry season load of TSS is less substantial,
TSS export from this residential catchment will still impact downstream waters.
This study, in a residential community in southern California, showed that significant
nutrients loss could occur in an urban area with non-storm surface flows in a semi-arid region.
The previously mentioned urban runoff study, in the Ballona Creek Watershed, showed that dry
weather flows could contribute up to 32% of annual TN loads and 6% of annual TP loads. Total
suspended solids contributions during dry weather were shown to be 2% of annual contributions
(McPherson et al., 2005). Recent studies confirm that loading estimate uncertainty can be
reduced by compiling data representing numerous observations over time and that increased
sampling frequency is especially important in small watersheds (Kirchner et al., 2004; Stein and
Ackerman, 2007). Using intensive sampling techniques, high daily variability in nutrient export
rates was seen in this study; illustrating elevated dry season nutrient concentrations caused by
reclaimed water use and transient events.
35
Table 6. Comparisons of estimated nutrient and sediment export rates from this study and other residential runoff studies.
Land Use TN (kg ha-1yr-1)
TP (kg ha-1yr-1)
TSS (kg ha-1yr-1) Sampling Location Study Area Reference
Residential 23.9 2.3 387
Automated flow-
weighted storm
runoff for 69 events
Nuese River Basin, NC
2.54 ha 25% ISAb
2-10% slopes
sandy loam humid
subtropical
(Line, 2002)
Residential 6.0 0.4 - Storm sampling
Charlotte and Mecklenburg County, NC
humid subtropical
(Bales et al., 1999)
Residential 6.7 0.96 - Automated
storm sampling of 43 events
Chesapeake Bay
62.11 ha (2 sites)
18% ISA humid
subtropical
(Hartigan et al., 1983)
Residential 8.4 1.3 - Storm Sampling Nationwide 81 sites in
22 cities (U.S.EPA
, 1983)
Developed 5.0-9.72 0.45-1.5 - Literature Review -
78 individual
studies
(Dodd, 1992)
Single Family Residential
20.20a 2.34a 97.13a
Automated time
sensitive intensive sampling
for 1 week during dry
weather
Aliso Creek Watershed,
CA
28.13 ha 15-30% slopes
56% ISAb clayey
semi-arid
This study
aExport rates are in (kg ha-1ds-1) (ds= dry season of 153 days) bISA denotes Impervious Surface Area
36
4. Conclusion
Several important ideas are brought to light by the results of this study. First, intensive
sampling can capture temporal changes that are important in correctly describing residential
runoff. Next, increasing specificity when describing urban land uses will make it easier to draw
comparisons and predict nutrient losses as anthropogenic activities vary between these land uses.
Lastly, dry season or baseflow contributions should be evaluated, especially in the arid southwest
if water resources are to be managed effectively.
This study illustrates the variability in nutrient concentrations on a temporal scale. The
intensive sampling method utilized discovered fluxes in nutrient concentrations, while
highlighting the impact of transient anthropogenic activities on a catchment scale. Through
intensive sampling it was discovered that the use of reclaimed water during the hours of 10:00
p.m. and 5:00 a.m. was contributing to nutrient losses within the catchment. Unexplained events
within the residential catchment resulted in higher N levels at the beginning of the intensive
sampling period, caused a sudden increase in TSS and TP during the middle of the intensive
sampling period, and resulted in elevated nutrient concentrations. According to the results of this
study, if samples were instead collected using grab samples during normal work hours (8:00 a.m.
to 4:00 p.m.), mean nutrient export would most likely be underestimated as sampling would take
place during times of lowest nutrient concentrations and lowest flow. Intensive sampling and
diurnal patterns in nutrient loading from this site illustrate the weaknesses of standard methods of
gathering water quality data.
This data shows that urban residential land use can have a negative impact on water
quality and that variability in data requires the use of small-scale water quality assessments that
more specifically categorize and describe land use. When compared to other urban runoff
37
studies, data from this study showed high mean dry weather nutrient concentrations as well as
seasonal export rates that exceeded most annual loading rates. The results illustrate the need to
conduct nutrient loading studies at a local catchment scale to create a more comprehensive
picture of nutrient loading that considers climate, geography, management, impervious surface
area, and human activity. Simply classifying land as urban/developed does not provide enough
useful information about the land use to accurately predict potential water quality problems.
Finally, this study demonstrates that human activities, irrigation schedules, and source of
irrigation water, are the most important factors affecting nutrient loading in this semi-arid
residential catchment during the dry season. Seasonality in water quality constituents and
nutrient export has been observed in other studies and is extremely important in the arid
southwest. Much of the previous work done to quantify nutrient exports has focused on storm
loads as the “first flush” phenomenon has been deemed the primary mechanism of nutrient
losses. This may be less true for regions where 80% of flows occur under dry conditions.
Differentiation between dry and wet season nutrient export can provide valuable insight for
environmental planning and watershed management.
38
References Andrews, G., 1998. Gardening and Water Quality Protection: Understanding Nitrogen Fertilizers, in: Service, O.S.U.E. (Ed.), Corvallis, Oregon.
Asano, T., Tchobanglous, G., 1987. Municipal wastewater treatment and effluent utilization for irrigation. FAO, Rome.
Atasoy, M., Palmquist, R.B., Phaneuf, D.J., 2006. Estimating the effects of urban residential development on water quality using microdata. Journal of Environmental Management 79, 399-408.
Bales, J.D., Weaver, J.C., Robinson, J.B., 1999. Relation of Land Use to Stream Flow and Water Quality at Selected Sites in the City of Charlotte and Mecklenburg County, North Carolina.
Barber, L.B., Murphy, S.F., Verplanck, P.L., Sandstrom, M.W., Taylor, H.E., Furlong, E.T., 2005. Chemical Loading into Surface Water along a Hydrological, Biogeochemical, and Land Use Gradient:‚Äâ A Holistic Watershed Approach. Environmental Science & Technology 40, 475-486.
Beckert, K., Fisher, T., O’Neil, J., Jesien, R., 2011. Characterization and Comparison of Stream Nutrients, Land Use, and Loading Patterns in Maryland Coastal Bay Watersheds. Water, Air, & Soil Pollution 221, 255-273.
Bennett, E.M., Carpenter, S.R., Caraco, N.F., 2001. Human Impact on Erodable Phosphorus and Eutrophication: A Global Perspective. BioScience 51, 227-234.
Bergström, A.-K., 2010. The use of TN:TP and DIN:TP ratios as indicators for phytoplankton nutrient limitation in oligotrophic lakes affected by N deposition. Aquatic Sciences - Research Across Boundaries 72, 277-281.
Brezonik, P.L., Stadelmann, T.H., 2002. Analysis and predictive models of stormwater runoff volumes, loads, and pollutant concentrations from watersheds in the Twin Cities metropolitan area, Minnesota, USA. Water Research 36, 1743-1757.
Brion, G., Brye, K.R., Haggard, B.E., West, C., Brahana, J.V., 2011. Land-use effects on water quality of a first-order stream in the Ozark Highlands, mid-southern United States. River Research and Applications 27, 772-790.
Brown Gaddis, E.J., Vladich, H., Voinov, A., 2007. Participatory modeling and the dilemma of diffuse nitrogen management in a residential watershed. Environmental Modelling & Software 22, 619-629.
Bureau, U.S.C., 2012. Aliso Viejo, California Quick Facts.
Caccia, V.G., Boyer, J.N., 2007. A nutrient loading budget for Biscayne Bay, Florida. Marine Pollution Bulletin 54, 994-1008.
39
California, R.o.t.U.o., 2006. Quality Assurance Project Plan: Evaluating Best Management Practices (BMPs) Effectiveness to Reduce Volumes of Runoff and Improve the Quality of Runoff from Urban Environments. Regents of the University of California, Davis, CA.
Carpenter, S.R., Caraco, N.F., Corell, D.L., Howarth, R.W., Sharpley, A.N., Smith, V.H., 1998. Nonpoint pollution of surface waters with phosphorus and nitrogen. Issues in Ecology 8, 559-568.
CDM, 2009. Baseline Environmental Conditions and Future Without-Project Conditions Report-Aliso Creek Mainstem Ecosystem Restoration Study Orange County, California, in: US Army Corps of Engineers, L.A.D.C.o.O.-O.W. (Ed.). US Army Corps of Engineers & County of Orange- OC watersheds, Irvine, CA.
Chua, L.H.C., Lo, E.Y.M., Shuy, E.B., Tan, S.B.K., 2009. Nutrients and suspended solids in dry weather and storm flows from a tropical catchment with various proportions of rural and urban land use. Journal of Environmental Management 90, 3635-3642.
Conley, D.J., 2000. Biogeochemical nutrient cycles and nutrient management strategies. Hydrobiologia 410, 87-96.
Conley, D.J., H.W. Pearl, R.W. Howarth, D.F. Boesch, S.P. Seitzinger, K.E. Havens, C. Lancelot, and G.E. Likens, 2009. Controlling eutophication: Nitrogen and phosphorus. Science, 1014-1015.
Consulting, M.E., 2007. Final Report of Geotechnical Evaluation for Environmental Impact Report. Proposed Aliso Creek Golf Course and Resort., Laguna Beach, California.
Coulter, C.B., Kolka, R.K., Thompson, J.A., 2004. Water quality in agricultural, urban, and mixed land use watersheds. Journal of the American Water Resources Association 40, 1593-1601.
County, O., 2006. Proposed Model for 2007 Aliso Creek Watershed Action Plan.
Crompton, C., 2006. Hydrologic Data Report 2004-2005 Season. County of Orange Resources and Development Management Department.
Daroub, S.H., Stuck, J.D., Lang, T.A., Diaz, O.A., 2002. Particulate Phosphorus in the Everglades Agricultural Area: Transport Mechanisms, in: Extension, U.o.F.I. (Ed.), Gainesville, Florida.
Diaz, R.J., and R. Rosenberg, 2008. Spreading dead zones and consequences for marine ecosystems. Science, 926-929.
District, M.N.W., 2011. Aliso Viejo Water Use Data, in: Haver, D. (Ed.), Water Use Data ed, Aliso Viejo, CA.
District, M.N.W., 2012. Drinking Water Quality Report.
40
Dodd, R.C., McMahon, Gerard., Stichter, Steven., 1992. Watershed Planning In the Albemarle-Pamlico Estuarine System: Average Annual Nutrient Budgets. Research Triangle Institute, Research Triangle Park, NC.
Easton, Z.M., Petrovic, A.M., 2004. Fertilizer source effect on ground and surface water quality in drainage from turfgrass. Journal of Environmental Quality 33, 645-655.
Endreny, T.A., Hassett, J.M., Wolosoff, S.E., 2005. Robustness of pollutant loading estimators for sample size reduction in a suburban watershed. International Journal of River Basin Management 3, 53-66.
Evanylo, G., Ervin, E., Zhang, X., 2010. Reclaimed water for turfgrass irrigation. Water 2, 685-701.
Fan, X., Cui, B., Zhang, K., Zhang, Z., Shao, H., 2012. Water Quality Management Based on Division of Dry and Wet Seasons in Pearl River Delta, China. CLEAN – Soil, Air, Water 40, 381-393.
Foley, J.A., DeFries, R., Asner, G.P., Barford, C., Nonan, G., Carpenter, S.R., Chapin, F.S., Coe, M.T., Daily, G.C., Gibbs, H.K., Helkowski, J.H., Holloway, T., Howard, E.A., Kucharik, C.J., Monfreda, C., Patz, J.A., Prentice, I.C., Ramankutty, N., Snyder, P.K., 2005. Global consequences of land use. Science 309, 570-574.
Forsberg, C., 1995. The large-scale flux of nutrients from land to water and the eutrophication of lakes and marine waters. Marine Pollution Bulletin 29, 409-413.
García-Pintado, J., MartÌnez-Mena, M., Barber·, G.G., Albaladejo, J., Castillo, V.M., 2007. Anthropogenic nutrient sources and loads from a Mediterranean catchment into a coastal lagoon: Mar Menor, Spain. Science of The Total Environment 373, 220-239.
Gin, K., Ramaswamy, U., Gopalakrishnan, A., 2011. Comparison of Nutrient Limitation in Freshwater and Estuarine Reservoirs in Tropical Urban Singapore. Journal of Environmental Engineering 137, 913-919.
Golterman, H.I., and De Oude N.T., 1991. Eutrophication of lakes, rivers, and coastal seas, The Handbook of Environmental Chemistry pp. 79-124.
Goonetilleke, A., Thomas, E., Ginn, S., Gilbert, D., 2005. Understanding the role of land use in urban stormwater quality management. Journal of Environmental Management 74, 31-42.
Grant, D.M., Dawson, Brian D., 1997. Isco Open Channel Flow Measurement Handbook, Fifth ed. ISCO.
Graves, G.A., Wan, Yongshan, Fike, Dana L., 2004. Water quality characteristics of storm water from major land uses in south Florida. Journal of the American Water Resources Association December, 1405-1419.
41
Gray, L., 2004. Changes in water quality and macroinvertebrate communities resulting from urban stormflows in the Provo River, Utah, U.S.A. Hydrobiologia 518, 33-46.
Groffman, P.M., Law, N.L., Belt, K.T., Band, L.E., Fisher, G.T., 2004. Nitrogen fluxes and retention in urban watershed ecosystems. Ecosystems 7, 393-403.
Hartigan, J.P., Quasenbarth, T.F., Southerland, E., 1983. Calibration of NPS Model Loading Factors. Journal of Environmental Engineering 109
Haver, D., 2011. Aliso Viejo Site Data.
Iwanyshyn, M., Ryan, M.C., Chu, A., 2008. Separation of physical loading from photosynthesis/respiration processes in rivers by mass balance. Science of The Total Environment 390, 205-214.
Johannesson, K., Andersson, J., Tonderski, K., 2011. Efficiency of a constructed wetland for retention of sediment-associated phosphorus. Hydrobiologia 674, 179-190.
Johnson, B., Yandora, K., Bryant, S.P.E., 1998. A Comprehensive Approach to Urban Stormwater Impact Assessment, in: Services, G.S.W. (Ed.), Greensboro, NC.
Kim, G., Yur, J., Kim, J., 2007. Diffuse pollution loading from urban stormwater runoff in Daejeon city, Korea. Journal of Environmental Management 85, 9-16.
King, K.W., Balogh, J.C., Harmel, R.D., 2007. Nutrient flux in storm water runoff and baseflow from managed turf. Environmental Pollution 150, 321-328.
Kirchner, J.W., Feng, X., Neal, C., Robson, A.J., 2004. The fine structure of water-quality dynamics: the (high-frequency) wave of the future. Hydrological Processes 18, 1353-1359.
Lado, M., Ben-Hur, M., 2009. Treated domestic sewage irrigation effects on soil hydraulic properties in arid and semiarid zones: A review. Soil and Tillage Research 106, 152-163.
Law, N., Band, L., Grove, M., 2004. Nitrogen input from residential lawn care practices in suburban watersheds in Baltimore county, MD. Journal of Environmental Planning and Management 47, 737-755.
Lee, S.-W., Hwang, S.-J., Lee, S.-B., Hwang, H.-S., Sung, H.-C., 2009. Landscape ecological approach to the relationships of land use patterns in watersheds to water quality characteristics. Landscape and Urban Planning 92, 80-89.
Lewis, D.B., Grimm, N.B., 2007. Hierarchical Regulation of Nitrogen Export from Urban Catchments: Interactions of Storms and Landscapes. Ecological Applications 17, 2347-2364.
Li, H.-e., Lee, J.H.-W., Cai, M., 2003. Nutrient Load Estimation Methods for Rivers. International Journal of Sediment Research 18, 346-351.
42
Lim, H.S., 2003. Variations in the water quality of a small urban tropical catchment: implications for load estimation and water quality monitoring. Hydrobiologia 494, 57-63.
Line, D.E., White, N.M., Osmond, D.L., Jennings, G.D., Mojonnier, C.B., 2002. Pollutant export from various land uses in the Upper Neuse River Basin. Water Environment Research 74, 100-108.
Manning, R., 1891. On the Flow of Waters in Open Channels and Pipes. Transactions of Civil Engineers of Ireland 20, 161-207.
Martinez, C.J., Clark, Mark w., 2009. Using Reclaimed Water for Landscape Irrigation, in: Extension, U.o.F.I. (Ed.), Gainesville, Florida.
McPherson, T.N., Burian, S.J., Stenstrom, M.K., Turin, H.J., Brown, M.J., Suffet, I.H., 2005. Dry and wet weather flow nutrient loads from a Los Angeles Watershed. Journal of the American Water Resources Association 41, 959-969.
Metcalf, Eddy an AECOM Company, I., Asano, T., Burton, F.L., Leverenz, H.L., Tsuchihashi, R., Tchobanoglous, G., 2007. Water Reuse. McGraw-Hill.
Metcalf, E., 1916. American Sewerage Practice, Disposal of Sewage. McGraw-Hill, New York.
Miguntanna, N.P., Goonetilleke, A., Egodowatta, P., Kokot, S., 2010. Understanding nutrient build-up on urban road surfaces. Journal of Environmental Sciences 22, 806-812.
NRCS, N.R.C.S.-. 2011. Web Soil Survey. USDA-NRCS.
Nyenje, P.M., Foppen, J.W., Uhlenbrook, S., Kulabako, R., Muwanga, A., 2010. Eutrophication and nutrient release in urban areas of sub-Saharan Africa -- A review. Science of The Total Environment 408, 447-455.
Obermann, M., Froebrich, J., Perrin, J.-L., Tournoud, M.-G., 2007. Impact of significant floods on the annual load in an agricultural catchment in the mediterranean. Journal of Hydrology 334, 99-108.
Pappas, P., 2009. Aliso Creek Watershed Land Use. Orange County Public Works, Orange County Public Works.
Pfeifer, L., Bennett, E., 2011. Environmental and social predictors of phosphorus in urban streams on the Island of Montréal, Québec. Urban Ecosystems 14, 485-499.
Pratt, B., Chang, H., 2012. Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales. Journal of Hazardous Materials 209–210, 48-58.
Rast, W., Lee, G., 1983. Nutrient Loading Estimates for Lakes. Journal of Environmental Engineering 109, 502-517.
43
Roberts, A.D., Prince, S.D., 2010. Effects of urban and non-urban land cover on nitrogen and phosphorus runoff to Chesapeake Bay. Ecological Indicators 10, 459-474.
Steele, M.K., W.H. McDowell, and J.A. Altkenhead-Peterson, 2010. Chemistry of Urban, Suburban, and Rural Surface Waters, Urban Ecosystem Ecology. American Society of Agromomy, Inc., Crop Science Society of America, Inc., Soil Science Society of America, Inc., Madison, WI, pp. 297-340.
Stein, E.D., Ackerman, D., 2007. Dry Weather Water Quality Loadings in Arid, Urban Watersheds of the Los Angeles Basin, California, USA. JAWRA Journal of the American Water Resources Association 43, 398-413.
Taebi, A., Droste, R.L., 2004. Pollution loads in urban runoff and sanitary wastewater. Science of The Total Environment 327, 175-184.
Tomer, M.D., Meek, D.W., Jaynes, D.B., Hatfield, J.L., 2003. Evaluation of nitrate-nitrogen fluxes from a tile-drained watershed in central Iowa. Journal of Environmental Quality 32, 642-653.
Tsegaye, T., Sheppard, D., Islam, K., Tadesse, W., Atalay, A., Marzen, L., 2006. Development of Chemical Index as a Measure of In-Stream Water Quality in Response to Land-Use and Land Cover Changes. Water, Air, & Soil Pollution 174, 161-179.
USEPA, 1983a. Chemical Methods for the Examination of Water and Wastes, Cincinnati, Ohio.
USEPA, 1983b. Results from the Nationwide Urban Runoff Program, in: Division, W.P. (Ed.), Final Report ed. U.S. Environmental Protection Agency, Washington, D.C.
Uusitalo, R., Yli-Halla, M., Turtola, E., 2000. Suspended soil as a source of potentially bioavailable phosphorus in surface runoff waters from clay soils. Water Research 34, 2477-2482.
Vadeboncoeur, M., Hamburg, S., Pryor, D., 2010. Modeled Nitrogen Loading to Narragansett Bay: 1850 to 2015. Estuaries and Coasts 33, 1113-1127.
Vaze, J., Chiew, F.H.S., 2002. Experimental study of pollutant accumulation on an urban road surface. Urban Water 4, 379-389.
Watersheds, O.C., 2012. 2012 Aliso Creek Watershed Workplan.
Yu, S., Yu, G.B., Liu, Y., Li, G.L., Feng, S., Wu, S.C., Wong, M.H., 2011. Urbanization impairs surface water quality: eutrophication and metal stress in the Grand Canal of China. River Research and Applications, n/a-n/a.
